TY - GEN
T1 - A novel-eye-tracking sensor for AR glasses based on laser self-mixing showing exceptional robustness against illumination
AU - Meyer, Johannes
AU - Schlebusch, Thomas
AU - Spruit, Hans
AU - Hellmig, Jochen
AU - Kasneci, Enkelejda
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/2/6
Y1 - 2020/2/6
N2 - The integration of eye-tracking sensors in next-generation AR glasses will increase usability and enable new interaction concepts. Consumer AR glasses emphasize however additional requirements to eye-tracking sensors, such as high integratability and robustness to ambient illumination. We propose a novel eye-tracking sensor based on the self-mixing interference (SMI) effect of lasers. In consequence, our sensor as small as a grain of sand shows exceptional robustness against ambient radiation compared to conventional camera-based eye trackers. In this paper, we evaluate ambient light robustness under different illumination conditions for video-based oculography, conventional scanned laser eye tracking as well as the SMI-based sensor.
AB - The integration of eye-tracking sensors in next-generation AR glasses will increase usability and enable new interaction concepts. Consumer AR glasses emphasize however additional requirements to eye-tracking sensors, such as high integratability and robustness to ambient illumination. We propose a novel eye-tracking sensor based on the self-mixing interference (SMI) effect of lasers. In consequence, our sensor as small as a grain of sand shows exceptional robustness against ambient radiation compared to conventional camera-based eye trackers. In this paper, we evaluate ambient light robustness under different illumination conditions for video-based oculography, conventional scanned laser eye tracking as well as the SMI-based sensor.
KW - AR glasses
KW - Low power eye-tracking
KW - Scanned laser eye-tracking
KW - Self-mixing-interference (SMI) sensor
UR - http://www.scopus.com/inward/record.url?scp=85085739182&partnerID=8YFLogxK
U2 - 10.1145/3379156.3391352
DO - 10.1145/3379156.3391352
M3 - Conference contribution
AN - SCOPUS:85085739182
T3 - Eye Tracking Research and Applications Symposium (ETRA)
BT - Proceedings ETRA 2020 Short Papers - ACM Symposium on Eye Tracking Research and Applications, ETRA 2020
A2 - Spencer, Stephen N.
PB - Association for Computing Machinery
T2 - 2020 ACM Symposium on Eye Tracking Research and Applications, ETRA 2020
Y2 - 2 June 2020 through 5 June 2020
ER -